Abnormal Heat Research Articles

Highly electrically conductive polyether composites with modified graphene

Abstract With the continuous improvement in the voltage, power, and capacity levels of high-voltage transmission and substation equipment, the problems of power loss and equipment failure caused by the abnormal heating of electrical contact parts are becoming increasingly severe. In the present study, to address this problem, graphite was exfoliated into thin layers of graphene using liquid-phase mechanical exfoliation, ultrasonic dispersion, and spray-drying techniques and incorporated into polyether composites to increase its electrical conductivity. The effects of the graphene content on the electrical conductivity, high-temperature resistance, wear reduction, and antiwear properties of the polyether composites were investigated. The results indicated that when 4 wt% graphene was added, the high-temperature resistance of the graphene–polyether composite (GPC) increased to 330 °C, and the volume resistivity decreased to 6.5 × 103 Ω·cm. Moreover, the contact-resistance coefficient of the GPC was reduced to 0.87 and 0.73 after it was coated on Cu and Al rows, respectively, which significantly increased the electrical conductivity of the electrical contact area. The most significant improvements in friction-reduction and antiwear properties were obtained for the polyether composites from this formulation. GPC has excellent electrical conductivity, high-temperature resistance, wear reduction, and antiwear properties and thus can substantially improve the quality of electrical connections when applied to electrical contact tips.

Study on combined thermal protection scheme integrating supercritical CO2 regenerative cooling and fuel film cooling used for scramjet engines

Supercritical CO2 closed-Brayton-cycle demonstrates considerable application potential on hypersonic vehicles, effectively addressing power supply issues during prolonged flights. However, the CO2 flow rate is strictly limited by the cycle’s cooling source (aviation kerosene), rendering traditional regenerative cooling inadequate for sufficiently cooling the scramjet engine. To address this challenge, this study proposes an integrated cooling scheme that combines regenerative cooling, ceramic thermal-protective layer, and fuel film cooling. A two-dimensional coupled numerical model was developed, simultaneously considering the convective heat transfer of supercritical CO2 and the shear mixing of supersonic fuel film. The results indicate that the high-enthalpy gas imposes an extreme aerodynamic heat load on the regenerative cooling channel wall, resulting in a notable deterioration in heat transfer for supercritical CO2. Implementing kerosene film cooling within the combustor can effectively mitigate the abnormal heat transfer behavior of supercritical CO2 and significantly reduce viscous dissipation heat within the gas boundary layer. By optimizing the fuel film injection layout, this combined cooling scheme reduced wall heat flux by 43% and temperature by over 400 K compared to traditional regenerative cooling, thus providing effective thermal protection for the scramjet engine.

Transformer abnormal heat accurate identification method based on AHIPDNet

Transformer is an important part of the power system, and its operation status is related to the safety and stability of the power system. In order to effectively improve the recognition accuracy of abnormal transformer heat, an improved YOLOv8 target detection algorithm model is proposed. The introduction of the SPD-Conv convolutional layer effectively improves the model’s recognition ability of the small target, and the introduction of the HAT hybrid attention mechanism and Dyhead multiple attention even if the information focusing on the abnormal hot spot is realized. The HAT hybrid attention mechanism and Dyhead multi-attention mechanism are introduced to better focusing of the model on the information of abnormal hot spots. Finally, the AHIPDNet transformer abnormal heat recognition method is formed. After experimental verification, the algorithm model achieves 93.1% recognition accuracy, which satisfies the demand of accurate recognition and localization of transformer’s abnormal heat in the field.

Regulatory factors and climatic impacts of marine heatwaves over the Arctic Ocean from 1982 to 2020

AbstractArctic warming has been substantially greater than that in the rest of the world and has had an important influence on the global climate. This study first explores the temporal and spatial evolutionary characteristics of marine heatwaves (MHWs) over the Arctic Ocean in multiyear ice (MYI), first‐year ice (FYI), and open‐water (OPW) regions from 1982 to 2020. MHWs in the Arctic Ocean show obvious spatial and seasonal variations, mainly occurring over the FYI region in the JAS (July–August–September, JAS), and their occurrences have a significant increasing trend in recent decades, accompanied by an abrupt increase since 2010. Furthermore, a multivariable network‐based method is adopted to delineate the relationship between different climatic factors and MHWs in the Arctic Ocean and the climatic impacts of MHWs. The results show that the correlations between different climatic factors and MHWs in JAS in 2010–2020 are generally stronger than those in 1982–2009, and the main influencing factors of MHWs in different ice covers are different. MHWs in the MYI region are mainly affected by freshwater dilution processes, such as sea‐ice concentrations (SIC), precipitation, and mixed‐layer salinity. For the FYI region, the 2‐m air temperature and total heat flux mainly affect MHWs by thermodynamic processes, and the 500‐hPa geopotential height affects MHWs mainly by large‐scale atmospheric circulation. The MHWs in the OPW region are mainly related to the SIC, 850‐hPa geopotential height, and 10‐m v‐wind, indicating that they are correlated with atmospheric processes and wind fields. MHWs in JAS are also revealed to reduce or delay the formation of sea ice in OND (October–November–December, OND) by storing more abnormal heat, indicating that unfrozen ocean surfaces may lead to enhanced Arctic amplification in the following seasons.

Expansion force signal based rapid detection of early thermal runaway for pouch batteries

With the extensive application of lithium-ion batteries in electric vehicles and energy storage stations, thermal safety issues have increasingly become the focus of public attention. To alleviate the safety concerns, a qualified battery management system (BMS) must be able to detect and warn of thermal abuse before it develops into a thermal runaway (TR). For the first time, the expansion force characteristics of the pouch battery module during the early heating stage of TR under typical working conditions are analyzed, which proves that the expansion force signal can reflect the internal abnormal heating earlier than the terminal voltage and the surface temperature, and has better noise resistance. Furthermore, the electromechanical coupling model (EmCM) is improved for more accurate open-loop expansion force estimation. On this basis, an expansion force based early TR rapid detection framework is proposed with less 3 min expend in tests, in which the Kalman filter ensures the stability and convergence/divergence of the observer estimation error, and the reliability of fault judgment is ensured by the adaptive threshold designed by the model structure.

Temperature and Physicochemical Properties of Abnormal Heating Composite Insulators.

Abnormal heating will reduce the insulation performance of composite insulators or even cause insulator fracture, and the abnormal heating phenomenon is more serious under high-humidity conditions. Therefore, in this paper, the voltage withstand test of abnormal heating composite insulators caused by aging and damp sheath, decay-like core rod, and contamination were carried out under different ambient humidity. The heating and discharge of composite insulators were observed by infrared thermal imager and ultraviolet imager, and its temperature characteristics were analyzed from the aspects of heating range, heating shape, and temperature difference. In addition, in order to study the abnormal heating mechanism of composite insulators, the micro-morphology, chemical groups and dielectric properties of the silicon rubber of composite insulators with aging and damp sheath and the decay-like core rod were also measured. It is found that the temperature characteristics of the three types of abnormal heating composite insulators are different, and the temperature difference increases with the increase of humidity. The deterioration of silicone rubber and core rod material is the internal reason for the abnormal heating of composite insulators, and high-humidity conditions will exacerbate the heating phenomenon.

Neuropathic Pain and Clinical Sensory Testing in Young Patients with Sickle Cell Disease

Abstract Background The pathophysiology of pain in sickle cell disease (SCD) is complex and not fully understood. Neuropathic pain (NP) is an emerging theory of chronic pain in SCD. Nevertheless, assessment of NP is not a part of standard care of patients with SCD. Aim and Objectives To study the frequency of neuropathic pain among young patients with SCD by ID-P questionnaire and Clinical Sensory Testing (CST). Patients and Methods In this cross-sectional study Patients with SCD were recruited and data were collected on sociodemographic and clinical criteria of the disease. ID Pain (ID-P) questionnaire was used as a screening tool for NP. We performed a bedside clinical sensory testing (CST) including cold, warm, and pressure detection, cold, heat, mechanical and pressure pain threshold. Results Fifty-six participants were screened for eligibility and twelve of them were excluded; ten had stroke and two patients were diabetic. A total of 44 participants (25 males and 19 females) were included, their mean age was 12.4 years (SD 4.8; range 5.9-25 years). Screening of NP using the ID-P questionnaire revealed that 22.7% of the study cohort likely had NP. On the other hand, 34% of the participants had abnormal CST; 10 patients (22.7%) had abnormal mechanical pain threshold, 6 (13.6%) showed abnormal cold pain threshold, 2 (4.5%) had abnormal heat pain threshold and 2 (4.5%) with abnormal pressure threshold, while only one patient had delayed cold detection. Conclusion Neuropathic pain, as assessed by ID-P questionnaire and CST, is not uncommon in young patients with SCD.

Abnormal Magnetic Phase Transition in Mixed-Phase (110)-Oriented FeRh Films on Al2O3 Substrates via the Anomalous Nernst Effect.

Iron rhodium (FeRh) undergoes a first-orderanti-ferromagnetic to ferromagnetic phase transition above its Curie temperature. By measuring the anomalous Nernst effect (ANE) in (110)-oriented FeRh films on Al2O3 substrates, the ANE thermopower over a temperature range of 100-350 K is observed, with similar magnetic transport behaviors observed for in-plane magnetization (IM) and out-of-plane magnetization (PM) configurations. The temperature-dependent magnetization-magnetic field strength (M-H) curves revealed that the ANE voltage is proportional to the magnetization of the material, but additional features magnetic textures not shown in the M-H curves remained intractable. In particular, a sign reversal occurred for the ANE thermopower signal near zero field in the mixed-magnetic-phase films at low temperatures, which is attributed to the diamagnetic properties of the Al2O3 substrate. Finite element method simulations associated with the Heisenberg spin model and Landau-Lifshitz-Gilbert equation strongly supported the abnormal heat transport behavior from the Al2O3 substrate during the experimentally observed magnetic phase transition for the IM and PM configurations. The results demonstrate that FeRh films on an Al2O3 substrate exhibit unusual behavior compared to other ferromagnetic materials, indicating their potential for use in novel applications associated with practical spintronics device design, neuromorphic computing, and magnetic memory.

Using benzonaphthothiophenes to trace paleo-oil migration directions in the Ediacaran-Cambrian reservoirs of the central Sichuan Basin

Benzonaphthothiophenes (BNTs) are important organosulfur compounds in oil, and their concentrations and [2,1]/([2,1] + [1,2])BNT ratio have been used as migration tracers. Here we focus on the applicability of BNTs as migration tracers for abnormally heat-altered paleo-oil reservoirs. For this purpose, 57 pyrobitumen samples from the Ediacaran to Cambrian dolomite reservoirs in the central Sichuan Basin were collected and detected by gas chromatography-mass spectrometry. The results showed that most pyrobitumens of the studied samples are characterized by high concentrations of unsubstituted polycyclic aromatic hydrocarbons (PAHs), high values of fluoranthene/PAHs, pyrene/PAHs, fluoranthene/(fluoranthene + pyrene), benzofluoranthene/(benzofluoranthene + benzopyrene), and unsubstituted-to-methylated aromatic ratios due to the alteration by abnormal heating. These pyrobitumens have high concentrations of BNTs, and their three isomers show a pattern of [2,1] > [1,2] > [2,3]BNT. The BNTs concentrations display a good positive relationship with the concentrations of the abnormal heating-related PAH, while [2,1]/([2,1] + [1,2])BNT ratio has no correlation with the abnormal heating-related indices, suggesting that abnormal heating of the paleo-oil reservoirs lead to the enrichment of BNTs but has a limited effect on [2,1]/([2,1] + [1,2])BNT ratio. Moreover, [2,1]/([2,1] + [1,2])BNT ratio seem to be not affected by kerogen type and depositional environment, but increases with source rock maturity. Therefore, the [2,1]/([2,1]+[1,2])BNT is still an effective migration tracer for abnormally heated reservoirs. This ratio was applied as migration tracer in the studied area. The result suggests that the paleo-oil primarily migrated from west depression to east bulges, followed by the direction from northwest to southeast, which is congruent with the geological setting and exploration practice, demonstrating the applicability of this parameter for abnormally heat-altered oil reservoirs.

Microstructure, hardness and creep properties for P91 steel after long-term service in a ultra-supercritical power plant

3 P91 pipes enduring 5∼6 × 104 h service had been found in an ultra-supercritical power plant. Hardness tests, microstructure observation(OM, SEM/EBSD, TEM/EDS) and creep rupture tests were performed, and the relationship between hardness, microstructure and creep rupture strength were discussed. Results showed that 1 of the 3 pipes still featured lath martensite, and its mechanical properties complied with relevant criteria. Other 2 pipes were characteristic of a mixture of ferrite and highly recovered martensite. Their hardness and creep rupture strength experienced severe degradation. Laves phase was observed in all 3 pipes. The most distinctive feature of the 2 low hardness pipes was their coarse and intragranularly distributed M23C6. This might be caused by abnormal heat treatments which could lead to the mixed microstructure of martensite and ferrite, and this kind of microstructure would degrade fast during service. Thus the low hardness had nothing to do with the precipitation of Laves phase.

Research on the division of heat dissipation spaces for multiple heat sources based on the adiabatic characteristic of heat flow lines

Due to the pressing need for compact layouts, the spacing between high-power devices is gradually decreasing, making the mutual influence between multiple heat sources unavoidable. Therefore, this paper proposes a method based on the adiabatic characteristics of heat flow lines and their convergence positions to evaluate the rationality of the thermal space design of each heat source. This method has been validated for applicability in one-dimensional, two-dimensional, and three-dimensional multi-heat-source conjugate convection heat transfer. Heat flow lines have significant advantages in describing energy flow, as they align with the direction of the temperature gradient. In thermal spaces with adiabatic boundaries or mutual influences between multiple heat sources, heat flow lines converge at certain positions. The relationship between adiabatic boundaries and heat flow line convergence positions has been studied, and a more interpretative decoupling scheme for multi-heat-source systems has been proposed. The main feature of this scheme is the separation of each heat source in the same steady-state thermal space and assigning adiabatic boundaries to the solid partition surfaces, allowing efficient observation of the thermal conditions of individual heat sources and targeted layout optimization. Results indicate that this method can utilize changes in heat flow line convergence positions to assess current thermal conditions and can be used to compare the thermal performance of different shaped heat sinks. Simulation results show that under the same mass conditions, thin-fin heat sinks perform 47 % better than thick-fin heat sinks, providing a more comprehensive and intuitive assessment compared to metrics such as thermal resistance and average temperature. The proposed method offers new ideas for multi-heat-source layout optimization, heat flow control, multi-heat-source partitioned simulation, and abnormal heating detection in multiple heat sources.

Thermal Imaging-Based Abnormal Heating Detection for High-Voltage Power Equipment

Thermal infrared imaging could detect hidden faults in various types of high-voltage power equipment, which is of great significance for power inspections. However, there are still certain issues with thermal-imaging-based abnormal heating detection methods due to varying appearances of abnormal regions and complex temperature interference from backgrounds. To solve these problems, a contour-based instance segmentation network is first proposed to utilize thermal (T) and visual (RGB) images, realizing high-accuracy segmentation against complex and changing environments. Specifically, modality-specific features are encoded via two-stream backbones and fused in spatial, channel, and frequency domains. In this way, modality differences are well handled, and effective complementary information is extracted for object detection and contour initialization. The transformer decoder is further utilized to explore the long-range relationships between contour points with background points, and to achieve the deformation of contour points. Then, the auto-encoder-based reconstruction network is developed to learn the distribution of power equipment using the proposed random argument strategy. Meanwhile, the UNet-like discriminative network directly explores the differences between the reconstructed and original image, capturing the deviation of poor reconstruction regions for abnormal heating detection. Many images are acquired in transformer substations with different weathers and day times to build the datasets with pixel-level annotation. Several extensive experiments are conducted for qualitative and quantitative evaluation, while the comparison results fully prove the effectiveness and robustness of the proposed instance segmentation method. The practicality and performance of the proposed abnormal heating detection method are evaluated on image patches with different kinds of insulators.

Estimation of overcharge-induced degradation state in lithium-ion cells using differential thermal voltammetry and distribution of relaxation times

Overcharge is recognized as a significant factor contributing to the degradation and potential thermal runaway of Li-ion cells. In this study, a novel approach is proposed to estimate the extent of overcharge-induced degradation in 18,650-type Li-ion cells with NCA cathodes and graphite anodes. Experimental results reveal abnormal heat generation and capacity loss due to overcharge-induced degradation. Using Differential Thermal Voltammetry (DTV) and Distribution of Relaxation Times (DRT) methods, ten degradation factors (DFs) that reflect the extent of degradation are identified. Through Pearson correlation analysis, the height of peak P1 in DTV and S2 in DRT are identified as the most indictive parameters to estimate degradation. Next, a predictive model based on Kriging deep learning method is developed using these parameters, which enables precise estimation. Validation results for the model demonstrate outstanding predictive accuracy, with a mean absolute percentage error (MAPE) of 3.25 % and a root mean square error (RMPE) of 3.62 %. The proposed methodology not only offers a robust approach to estimate overcharge-induced degradation of Li-ion cells, but also provides valuable insights for enhancing the monitoring and management capabilities of battery system.

A comparative study on abnormal heat transfer of supercritical CO2 heated in vertical tubes

The heat transfer characteristics of supercritical CO2 heated in vertical smooth tube are experimentally and numerically investigated. The results show that the M-shaped velocity corresponds to heat transfer enhancement (HTE) at G = 100 kg/m2s, q = 20 kW/m2, and the heat transfer coefficient (HTC) is 15% higher than that of normal heat transfer (NHT). While, the M-shaped velocity causes significant heat transfer deterioration (HTD) before the Tpc at G = 278 kg/m2s, q = 35 kW/m2, and the HTC of HTD is 28%–42% of that in NHT. According to the numerical analysis on the M-shaped flow structure, it reveals that the zero-velocity gradient point of abNHT (HTE and HTD) always falls into the buffer layer (5 < y+ < 30). While, the zero-velocity gradient point of the heat transfer recovery (HTR) is in the log-law region (30 < y+ < 60). The u/u0 of the zero-velocity gradient point of HTE are larger than 1.35. The cross-section turbulent kinetic energy structure shows that smaller TKE in the near-wall region is the dominant factor for HTD and larger TKE in the core region is the dominant factor for HTE.

A graph learning approach for automatic subsurface defects segmentation in building façade using RGB and infrared images

Infrared thermal imaging technology provides a non-destructive and automated inspection solution for analyzing building facades. However, conventional methods that rely on detecting subsurface defects through abnormal heat loss often suffer from the limitation of misidentifying other materials present on the building facade. To address this challenge, this study proposes a graph learning approach for segmentation of subsurface defects by integrating both visual and thermal information. The proposed methodology encompasses several key steps. Firstly, the infrared image is partitioned into internally connected superpixels with similar characteristics using a linear iterative clustering algorithm. Subsequently, these superpixels are employed as nodes to construct a weighted undirected graph. The edges of the graph are defined based on the connectivity of superpixels in the image plane, while the weights are determined by the Wasserstein distance between each node. Furthermore, a multimodal graph reuse technique is introduced to construct a new graph based on an RGB image, thereby incorporating additional visual information. By defining the defect as tightly connected in the RGB graph but loosely connected in the infrared graph, the segmentation of defects involving multiple materials is formulated as a multi-graph N-cut problem. The feasibility and effectiveness of the proposed method are demonstrated through laboratory testing conducted on concrete specimens, as well as on-site monitoring carried out on a tiled building façade.

EGCG Alleviates the Aging Toxicity Induced by 3-MCPD via IIS Pathway in Caenorhabditis elegans with Abnormal Reproduction and Heat Shock Protein.

This study aimed to investigate the mitigation effect of epigallocatechin gallate (EGCG) on aging induced by 3-monochloropropane-1,2-diol (3-MCPD) in Caenorhabditis elegans, evaluate health indicators during the process, and reveal the underlying mechanism through transcriptomics and identification of mutants. The results showed that EGCG alleviated the declined fertility, shortened lifespan, reduced body size, weakened movement, increased reactive oxygen species and lipofuscin, and damaged antioxidative stress response and excessive heat shock proteins caused by 3-MCPD. Transcriptomics study indicated that treatment with 3-MCPD and EGCG altered gene expression, and gene mutants confirmed the involvement of insulin/IGF-1 signaling pathway in mediating the process that EGCG alleviated the aging toxicity induced by 3-MCPD. The study showed that EGCG alleviated the aging toxicity induced by 3-MCPD.

Preparation method of reversible temperature indicating patch for temperature self-detection of power equipment and its properties

Abstract The problem of thermally induced defects in power equipment is prominent, affecting the safe and stable operation of the power grid. To detect abnormal heating in time, a reversible temperature-indicating patch measurement for temperature self-detection of power equipment is proposed, and its performance is analyzed and studied. The results show that the reversible thermochromic patch prepared with heat-sensitive red as the hidden colorant, dodecyl gallate as the color rendering agent, and tetradecane as the solvent has the color change characteristic of “light color at low temperature and deep color at high temperature”, and its color-changing temperature interval is 42°C ∼ 52°C. The color-changing performance of the materials with different quality ratios is different, from which the optimal ratio of the color-changing materials is selected as thermochromic red: lauryl gallate: tetradecanol=1:7:30. To facilitate the application of the color-changing materials on-site, the color-changing materials are encapsulated by melt adsorption sealing technology, and the temperature indicating patches with good color-changing reversibility are prepared. The research results can provide a reference for the field application of reversible color-changing materials for temperature self-detection of power equipment.

Recent research and developments of degradation assessment and its diagnosis methods for solar PV plant: a review

The world is moving forward to a transition in the form of increasing the contribution of renewable energy sources in the energy sector, and among these, solar photovoltaic-based power generation is catching pace. Several factors are responsible for the lowering of outputs due to different degradation causes such as hotspots, corrosion, humidity, ultraviolet (UV) irradiation, temperature effects, dust, aging, weathering, yellowing, snail trails, discoloration, junction box failure, delamination, cracks, and faults from the solar photovoltaic (PV) plants. This paper presents a comprehensive review of the various form of degradation and their implications on solar PV power plant performance. The review has been carried out considering the different degradation causes and their identification methods in solar PV plant. Further, the analysis has been done on the basis of the earlier studies to understand the rates of degradation for various solar PV power plants in various climatic conditions. The PV technologies used in solar power plants are also responsible for the change in the performance of power plants over time; therefore, degradation based on different solar PV cell technologies is also analyzed. The visual inspection tools like thermal imaging with IR cameras help identify areas with abnormal heat patterns, indicating potential issues like cell or interconnect failures, loose electrical connections, or bypass diode malfunctions while EL cameras are used to identify low-level electrical excitation and defects such as cracks, hotspots, and cell-level degradation.

The Adhesion Characteristics and Aging Performance of Reversible Color-Changing Coatings for Self-Detection of Temperature by Power Equipment

In order to detect abnormal heat generation in time, a reversible color-changing coating temperature measurement method is proposed for self-detection of temperature by power equipment, and its adhesion characteristics and aging performance were analyzed. The results showed that the reversible color-changing coating prepared with crystalline violet lactone as the colorant, bisphenol A as the color developer, octadecanol as the solvent, and RTV-II as the base paint can meet the requirements of self-detection of temperature by power equipment with its adhesion performance. The accelerated aging tests using high temperature, light and humidity were carried out in the laboratory, and we concluded that the deterioration degree of the color-changing coating was positively correlated with the temperature. Light can accelerate the aging rate of reversible color-changing coatings, and the degradation process of the coating was significantly accelerated under UV light. The effect of humidity on the coating was not significant. The degradation of the coating after aging for 288 h under indoor conditions was small, while it was accelerated under outdoor natural conditions. This research can provide a reference for the on-site application of reversible color-changing coatings for self-detection of temperature by power equipment.

SATELLITE MONITORING OF AGRICULTURAL CROP DEVELOPMENT ASSESSMENT

Climate changes are increasingly affecting the agricultural industry of European countries, modern methods of satellite data offer practical solutions for monitoring the state of development of agricultural crops with the possibility of further forecasting yields. Agriculture directly depends on natural resources and climate. Negative changes in weather conditions, such as abnormal heat, floods, forest and peat fires, dry winds, ice significantly reduce crop yields. For example, high temperatures disrupt the ability of plants to receive and use moisture. This is a serious threat to food security, as agriculture is a source of livelihood for a large number of people. Satellite data is an effective solution to increase agricultural productivity and yield. This study aims to develop an information technology of satellite monitoring for agricultural plant development with an intelligent fuzzy system.